The present invention relates to surveillance devices.
Historically, visual surveillance systems were designed as permanent additions to existing site infrastructure, and they were intended to protect assets and monitor activity in and around buildings and grounds by adding audio-video capture. They typically would extend existing security installations (comprised of specialty sensors for contact, motion, heat, chemicals, water, etc.), but they might also entail entirely new custom installations. Because of the significant investment of time and complexity of installing, such systems were generally permanent and unchanging without major redesign. As a result, cameras needed to be carefully placed at predefined, strategic locations within or on buildings or on poles and other structures that could provide good vantage points. And until recently sensors were hardwired to data collection nodes and monitoring centers, so reconfiguration was difficult and time consuming.
One advantage of such fixed-location/stationary camera installations is that camera positions can be precisely known, and therefore the relative positions of objects and events detected in the scene can be precisely inferred. Temporal synchronization is relatively straightforward as cameras operate on a common clock. And knowing the exact positions of cameras relative to one another facilitates reliable integration of events moving between the fields-of-view (FOVs) of different cameras.
The advent of low-cost, hi-res digital cameras and the emergence of robust wireless broadband technologies such as WiFi and 4G/5G enable more flexible positioning and repositioning of cameras. However, stationary cameras remain susceptible to occlusions (both permanent and transitory), adverse lighting effects (such as glare and shadowing), and lack of sufficient resolution at distance. As a consequence, some modern surveillance systems have come to incorporate mobile cameras—i.e., cameras mounted on moving platforms—which can provide more comprehensive data gathering and more detailed views of a particular area or situation.
Mobile platforms may be distinguished according to their navigation control paradigm (manually driven, tele-operated, or autonomously driven) and according to their operating environment (air, land, or sea). Waterborne vehicles are generally an exclusive concern of naval operations and have a different set of concerns from autonomous ground vehicles (AVGs). While airborne vehicles might ultimately enhance site surveillance, they are currently subject to shifting FAA regulations and local-varying legal operating restrictions.
Mobile camera platforms are capable of moving closer to events as needed and to attain better vantage points as circumstances permit. However it remains a major challenge to determine the exact location of the mobile platform and its cameras at any instant, especially while moving. While significant progress has been made using modern techniques such as sensor-fusion and SLAM (Simultaneous Localization and Mapping), large uncertainties can still be present due to drift of inertial sensors and lack of sufficient positional resolution of public GPS.
This lack of accurate positioning has prompted some vendors to develop and install proprietary differential positioning systems. But such proprietary differential positioning systems tend to be site-specific and are therefore brittle and costly to deploy. More recently, some vendors have announced visual surveillance products that are stationary or mobile, but these are not tightly integrated into a unified solution. They typically act as independent components with specific duties applicable to specific situations, and any integration happens through the backend.
More recently, there has been activity in so-called robot swarms. This trend has found particular appeal in the unmanned airborne vehicle (UAV) arena, and it can be viewed as an extension of classic parallel processing paradigms (in particular, SPMD—Single Program Multiple Data—models) to robotics. Swarms are generally motivated by biological examples (ants, bees, etc.), where multiple identical agents with the same capabilities realize a multiplicative advantage by each working on a small chunk of the problem. In surveillance, this typically means sub-regions of the area to be surveilled would be assigned to swarm members in 1-to-1 or 1-to-many-fashion.
Needless to say, coordination of a swarm's tasking can be complex. More significantly, since all agents have the same capabilities (both strengths and weaknesses), the swarm is not able to directly compensate for individual shortcomings. Instead, the swarm works through redundancy of effort, seeking to overwhelm the problem through brute-force rather than exploiting complementary capabilities. In addition, the swarm approach does not explicitly embody a means to rapidly deploy to a given site.
The foregoing and other objectives, features, and advantages of the invention will be more readily understood upon consideration of the following detailed description of the invention, taken in conjunction with the accompanying drawings.